AI Visibility Audit
Audit a public site for crawlability, schema coverage, answer extraction readiness, llms.txt presence, and other AI visibility signals.
Use this audit to surface the technical and structural issues that make it harder for AI search systems, answer engines, and citation workflows to understand your site.
A structured audit for the most practical signals that influence how easily your site can be discovered, parsed, and cited by modern answer systems.
How Visibility Audit is organized
Each tool page follows the same production-minded pattern: a clear promise, a constrained report structure, and a path into deeper services.
Discoverability
Fetchability, robots, sitemap, and canonical basics.
Structure
Headings, semantics, internal linking, and content extraction signals.
Trust signals
Entity clarity, bylines, references, freshness, and credibility cues.
Best use cases
What you get for free
How the Visibility Audit works
Each tool keeps the interaction simple on the surface, but the output is organized so teams can act on it quickly and understand what the score actually means.
Normalize the site root
The audit resolves the submitted URL to the homepage so it can compare the same baseline across sites.
Check discovery surfaces
It inspects robots.txt, sitemap.xml, llms.txt, and homepage reachability instead of pretending to crawl the entire site.
Translate signals into actions
The output groups the most practical structural and discoverability gaps into a short list of next steps.
Audit homepage discoverability, structure, and AI-readiness signals
Submit a public site URL to review root-level discoverability files, homepage structure, internal linking, schema presence, and answer-oriented content cues.
Audit a site
Enter a homepage or domain. The audit normalizes the target to the site root before checking discoverability and structure.
Site-level visibility snapshot
The report blends homepage structure checks with root-level discoverability files to create a practical AI visibility baseline.
No audit yet
Once you run the audit, this section will show discoverability checks, homepage structure signals, and the most important issues to fix first.
What to do after Visibility Audit
If the output looks directionally useful, the next step is usually turning the findings into implementation work, content changes, or a sharper audit scope.
Common questions
These pages are designed to rank for practical tool intent while still setting realistic expectations about what a lean v1 can and cannot claim.
Does this tool measure actual LLM market share or citation counts?
No. The v1 audit focuses on practical structural signals that influence whether a page is easier for AI systems to crawl, parse, and quote.
Will it crawl my whole site?
The shared framework is designed for a constrained crawl budget. That keeps response times and infrastructure costs reasonable for a free tool.
Keep exploring the toolkit
Each tool page can drive internal linking between adjacent user intents instead of behaving like an isolated landing page.
LLM Citation Checker
Evaluate whether a public page is structurally clear, quotable, and citation-friendly for LLMs and AI answer systems.
llms.txt Checker
Validate whether a site exposes a public llms.txt file, whether it can be parsed correctly, and whether its contents are useful.